A probabilistic approach for multi-objective clustering using game theory

Author(s):  
Mahsa Badami ◽  
Ali Hamzeh ◽  
Sattar Hashemi
2021 ◽  
Vol 135 ◽  
pp. 104896
Author(s):  
Sandra Maria Cardoso ◽  
Daniel Bezerra Barros ◽  
Eva Oliveira ◽  
Bruno Brentan ◽  
Lubienska Ribeiro

2012 ◽  
Vol 18 (3) ◽  
pp. 389-423 ◽  
Author(s):  
Faramak Zandi ◽  
Madjid Tavana ◽  
Aidan O’Connor

Market segmentation is essential to target efficaciously core-segment customers and to obtain a competitive advantage. Firms when confronted by the range of market segments, have difficulty in deciding the core-segment customers who are the most probable purchasers of their product and services. We propose a novel fuzzy group multi-criteria method for market entry and segment evaluation and selection. This proposed method provides a comprehensive and systematic framework that combines bi-level multi-objective optimization with real option analysis (ROA) and fuzzy cooperative n-person game theory. The contribution of the proposed segment evaluation and selection method is fivefold: (1) it addresses the gaps in the marketing literature on the efficacious and effective assessment of market segments; (2) it provides a comprehensive and systematic framework that combines bi-level multi-objective optimization with ROA and fuzzy cooperative n-person game theory; (3) it considers fuzzy logic and fuzzy sets to represent ambiguous, uncertain or imprecise information; (4) it does not insist on consensus but synthesizes a representative outcome based on qualitative judgments and quantitative data; and (5) it is applicable to national and international market segmentation. The practical application of this proposed framework illustrates the efficacy of the procedures and algorithms.


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